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ICANN
2007
Springer
14 years 3 months ago
Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
Shigeo Abe, Kenta Onishi
TIP
2008
128views more  TIP 2008»
13 years 9 months ago
Wavelet Frame Accelerated Reduced Support Vector Machines
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Matthias Rätsch, Gerd Teschke, Sami Romdhani,...
ICPR
2006
IEEE
14 years 10 months ago
On Kernel Selection in Relevance Vector Machines Using Stability Principle
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
Dmitry Kropotov, Nikita Ptashko, Oleg Vasiliev, Dm...
ICDM
2006
IEEE
118views Data Mining» more  ICDM 2006»
14 years 3 months ago
Generalizing Version Space Support Vector Machines for Non-Separable Data
Although version space support vector machines (VSSVMs) are a successful approach to reliable classification [6], they are restricted to separable data. This paper proposes gener...
Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, Ni...
IMSCCS
2006
IEEE
14 years 3 months ago
Parallel Multicategory Support Vector Machines (PMC-SVM) for Classifying Microcarray Data
Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of biological classification problems. However, the proc...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...